ABSTRACT
Epidemiological models, also known as host-agent-vector-environment models, are utilized in public health to gain insights into disease occurrence and to formulate intervention strategies. In this paper, we propose an epidemiological model that incorporates both conventional measures and tobacco endgame policies. Our model suggests that conventional measures focus on relationships among agent-vector-host-environment components, whereas endgame policies inherently aim to change or eliminate those components at a fundamental level. We also found that the vector (tobacco industry) and environment (physical and social surroundings) components were insufficiently researched or controlled by both conventional measures and tobacco endgame policies. The use of an epidemiological model for tobacco control and the tobacco endgame is recommended to identify areas that require greater effort and to develop effective intervention measures.
ABSTRACT
Objectives@#In this paper, we aimed to investigate the evolving debate over border closure in Korea during the coronavirus disease 2019 (COVID-19) pandemic, to address the main themes associated with border closure, and to discuss the factors that need to be considered when making such decisions. @*Methods@#We collated and reviewed previously conducted review studies on border closures during infectious disease outbreaks to derive relevant themes and factors. @*Results@#According to our systematic review on border closures and travel restrictions, the effects of such containment efforts are limited. We suggest considering the following factors when determining whether to impose border closure measures: (1) disease characteristics, (2) timeliness of implementation, (3) transmission delay and the basic reproduction number, (4) globalization and pandemics, and (5) social and economic costs. @*Conclusions@#Our assessment indicates that the effects of border closures are at best temporary and limited. Alternative measures must be contemplated and implemented to suppress the spread of COVID-19 in particular and infectious diseases more broadly.
ABSTRACT
Background@#The coronavirus disease 2019 (COVID-19) pandemic has posed significant global public health challenges and created a substantial economic burden. Korea has experienced an extensive outbreak, which was linked to a religion-related super-spreading event. However, the implementation of various non-pharmaceutical interventions (NPIs), including social distancing, spring semester postponing, and extensive testing and contact tracing controlled the epidemic. Herein, we estimated the effectiveness of each NPI using a simulation model. @*Methods@#A compartment model with a susceptible-exposed-infectious-quarantinedhospitalized structure was employed. Using the Monte-Carlo-Markov-Chain algorithm with Gibbs' sampling method, we estimated the time-varying effective contact rate to calibrate the model with the reported daily new confirmed cases from February 12th to March 31st (7 weeks). Moreover, we conducted scenario analyses by adjusting the parameters to estimate the effectiveness of NPI. @*Results@#Relaxed social distancing among adults would have increased the number of cases 27.4-fold until the end of March. Spring semester non-postponement would have increased the number of cases 1.7-fold among individuals aged 0–19, while lower quarantine and detection rates would have increased the number of cases 1.4-fold. @*Conclusion@#Among the three NPI measures, social distancing in adults showed the highest effectiveness. The substantial effect of social distancing should be considered when preparing for the 2nd wave of COVID-19.